Abstract: Fisheries surveys over broad spatial areas are crucial in defining and delineating appropriate fisheries management areas. Yet accurate mapping and tracking of fishing activities remain largely restricted to developed countries with sufficient resources to use automated identification systems and vessel monitoring systems. For many countries, the spatial extent and boundaries of fishing grounds are not completely known. We used satellite images at night to detect fishing grounds in the Philippines for fishing gears that use powerful lights to attract coastal pelagic fishes. We used nightly boat detection data, extracted by U.S. NOAA from the Visible Infrared Imaging Radiometer Suite (VIIRS), for the Philippines from 2012 to 2016, covering 1713 nights, to examine spatio-temporal patterns of fishing activities in the country. Using density-based clustering, we identified 134 core fishing areas (CFAs) ranging in size from 6 to 23,215 km2 within the Philippines’ contiguous maritime zone. The CFAs had different seasonal patterns and range of intensities in total light output, possibly reflecting differences in multi-gear and multi-species signatures of fishing activities in each fishing ground. Using maximum entropy modeling, we identified bathymetry and chlorophyll as the main environmental predictors of spatial occurrence of these CFAs when analyzed together, highlighting the multi-gear nature of the CFAs. Applications of the model to specific CFAs identified different environmental drivers of fishing distribution, coinciding with known oceanographic associations for a CFA’s dominant target species. This case study highlights nighttime satellite images as a useful source of spatial fishing effort information for fisheries, especially in Southeast Asia.

Abstract: Whereas monthly and annual nighttime light (NTL) composite datasets are being increasingly used to estimate socioeconomic status, use of the National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) Day/Night Band (DNB) daily data has been limited for detecting and assessing the impact of short-term disastrous events. This study explores the application of daily NPP-VIIRS DNB data in assessing the impact of three types of natural disasters: earthquakes, floods, and storms. Daily DNB images one month prior to and 10 days after a disastrous event were collected and a Percent of Normal Light (PNL) image was produced as the ratio of the mean DNB radiance of the pre- and post-disaster images. Areas with a PNL value lower than one were considered as being affected by the event. The results were compared with the damaged proxy map and the flood proxy map generated using synthetic aperture radar data as well as the reported power outage rates. Our analyses show that overall NPP-VIIRS DNB daily data are useful for detecting damages and power outages caused by earthquake, storm, and flood events. Cloud coverage was identified as a major limitation in using the DNB daily data; rescue activities, traffic, and socioeconomic status of the areas also affect the use of DNB daily data in assessing the impact of natural disasters. Our findings offer new insight into the use of the daily DNB data and provide a practical guide for researchers and practitioners who may consider using such data in different situations or regions.

Abstract: Disruptions to the circadian rhythm can lead to altered metabolism. Modification of thyroid function may be a reason why circadian misalignment may contribute to future metabolic disorders. We investigated whether circadian disruption through constant light (LL) can lead to variations in hormone levels associated with thyroid function. Mice were exposed to LL or a 12:12 Light:Dark (LD) cycle for 6 weeks; then glucose tolerance and thyroid hormone levels were measured at ZT 6 and ZT 18. There was day/night variation in glucose tolerance, but LL had no effect. LL reduced TSH, increased fT4, and abolished day/night variation in fT3 and leptin. These findings illustrate that LL alters thyroid-related hormones, providing evidence of a link between circadian disruption and thyroid function.

Abstract: Remotely sensed artificial lighting radiances at night can provide spatially explicit proxy measures of the magnitude of human activity. Satellite-derived nighttime light images, mainly provided by the Defense Meteorological Satellite Program (DMSP) and the Visible Infrared Imaging Radiometer Suite (VIIRS) day/night band (DNB), have been increasingly used to study demographic and socioeconomic activities for a wide range of issues—for instance, human population dynamics, economic growth, and urbanization process—at multiple scales. In practice, the lack of texture information regarding man-made surfaces would usually lead to substantial difficulty in delineating the spatial dynamics in human settlements due to the diverse distributions of artificial nocturnal lighting sources, which are closely related to the predominant land-use/land-cover (LULC) types and their evolutions. An understanding of how nighttime lighting signals respond to synchronous anthropogenic LULC changes, therefore, is crucially important for the spatiotemporal investigations of human settlement dynamics. In this study, we used DMSP-derived nighttime light (NTL) data and Landsat-derived LULC maps to quantitatively estimate the pixel-level responses of NTL signals to different types of human-induced LULC conversions between 1995 and 2010 across China. Our results suggest that the majority (>70%) of pixel-level LULC conversions into artificial lands (including urban, rural, and built-up lands) might show a statistically significant increase in nighttime brightness with an average >20 (in digital number, DN) step change in nighttime lights (dNTL), both of which are distinctly higher than that in the LULC conversions into non-man-made surfaces on the whole. A receiver operating characteristic (ROC) curve-based analysis implies that we might have an average chance of ~90% to identify the nationwide LULC conversions into man-made surfaces from all types of conversions through the observed changes in artificial nocturnal luminosity signals. Moreover, ROC curve-based analyses also yield two nation-level optimal dNTL thresholds of 4.8 and 7.8 DN for recognizing newly emerged three types of artificial lands and urban lands between 1995 and 2010 across the entire country, respectively. In short, our findings reveal fundamental insights into the quantitative connections between the anthropogenic LULC changes and the corresponding responses of synchronous nightlight signals at the pixel-level, which are generally essential for further applications of satellite-derived nocturnal luminosity data in the spatiotemporal investigations of human settlement dynamics.